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Plain-language answers to statistics questions people are asking. Have your own? Ask us.

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descriptive statistics 2 distributions 2 causal inference 1 confidence intervals 1 hypothesis testing 1 margin of error 1 normality 1 sampling 1 standard deviation 1 study design 1 time series 1

Interrupted time series vs event study vs difference-in-differences

All three estimate the effect of an intervention, but each builds its counterfactual differently. Here is how to tell them apart.

Read the answer → September 21, 2026

Is a normality test worth running on your data?

Normality tests answer the wrong question: with lots of data they flag harmless quirks, with little data they miss real problems. Here is what to do.

Read the answer → September 21, 2026

What does kurtosis actually tell you about your data?

Kurtosis describes how heavy a distribution's tails are, not how peaked it is. Here is how to read it, in plain language.

Read the answer → September 21, 2026

Where does the 1/sqrt(n) margin of error come from?

The rule that a poll has a margin of error of about 1/sqrt(n) is a short derivation, not a guess. Here it is step by step.

Read the answer → September 21, 2026

Why does standard deviation square the differences?

Squaring deviations makes variances add up, ties into least squares and the normal distribution, and keeps the math clean.

Read the answer → September 21, 2026

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